Joint detection-estimation of brain activity in functional MRI: a Multichannel Deconvolution solution, IEEE Transactions on Signal Processing, vol.53, issue.9, pp.3488-3502, 2005. ,
DOI : 10.1109/TSP.2005.853303
A fully Bayesian approach to the parcel-based detection-estimation of brain activity in fMRI, NeuroImage, vol.41, issue.3, pp.941-969, 2008. ,
DOI : 10.1016/j.neuroimage.2008.02.017
URL : https://hal.archives-ouvertes.fr/cea-00333624
Brain magnetic resonance imaging with contrast dependent on blood oxygenation., Proc. Natl ,
DOI : 10.1073/pnas.87.24.9868
Imaging neuroscience: Principles or maps?, Proc. Natl. Acad. Sci. USA, pp.796-802, 1998. ,
DOI : 10.1073/pnas.95.3.796
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC33800/pdf
Detecting Latency Differences in Event-Related BOLD Responses: Application to Words versus Nonwords and Initial versus Repeated Face Presentations, NeuroImage, vol.15, issue.1, pp.83-97, 2002. ,
DOI : 10.1006/nimg.2001.0940
Statistical parametric mapping, Functional Neuroimaging : Technical Foundations, pp.79-93, 1994. ,
DOI : 10.1007/978-1-4615-1079-6_16
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.8.3745
Empirical and substantive models, the Bayesian paradigm, and meta???analysis in functional brain imaging, Human Brain Mapping, vol.5, issue.4, pp.259-263, 1997. ,
DOI : 10.1002/(SICI)1097-0193(1997)5:4<259::AID-HBM10>3.3.CO;2-#
Parametric Analysis of fMRI Data Using Linear Systems Methods, NeuroImage, vol.6, issue.2, pp.93-103, 1997. ,
DOI : 10.1006/nimg.1997.0278
Modeling hemodynamic response for analysis of functional MRI time-series, Human Brain Mapping, vol.2, issue.4, pp.283-300, 1998. ,
DOI : 10.1002/(SICI)1097-0193(1998)6:4<283::AID-HBM7>3.0.CO;2-#
Modeling the hemodynamic response in single-trial functional MRI experiments, Magnetic Resonance in Medicine, vol.6, issue.4, pp.787-797, 1999. ,
DOI : 10.1002/(SICI)1522-2594(199910)42:4<787::AID-MRM22>3.0.CO;2-V
A Bayesian Time-Course Model for Functional Magnetic Resonance Imaging Data, Journal of the American Statistical Association, vol.55, issue.451, pp.691-719, 2000. ,
DOI : 10.1006/nimg.1995.1023
Bayesian Spatiotemporal Inference in Functional Magnetic Resonance Imaging, Biometrics, vol.22, issue.2, pp.554-562, 2001. ,
DOI : 10.1111/j.0006-341X.2001.00554.x
Fully Bayesian Spatio-Temporal Modeling of FMRI Data, IEEE Transactions on Medical Imaging, vol.23, issue.2, pp.213-231, 2004. ,
DOI : 10.1109/TMI.2003.823065
Comparison of two convolution models for fMRI time series, Neuroimage, vol.5, p.473, 1997. ,
Modeling the hemodynamic response in fMRI using smooth FIR filters, IEEE Transactions on Medical Imaging, vol.19, issue.12, pp.1188-1201, 2000. ,
DOI : 10.1109/42.897811
Robust Bayesian estimation of the hemodynamic response function in event-related BOLD fMRI using basic physiological information, Human Brain Mapping, vol.2, issue.1, pp.1-17, 2003. ,
DOI : 10.1002/hbm.10100
URL : https://hal.archives-ouvertes.fr/cea-00333748
Unsupervised robust nonparametric estimation of the hemodynamic response function for any fmri experiment, IEEE Transactions on Medical Imaging, vol.22, issue.10, pp.1235-1251, 2003. ,
DOI : 10.1109/TMI.2003.817759
URL : https://hal.archives-ouvertes.fr/cea-00333694
Estimation of the Hemodynamic Response in Event-Related Functional MRI: Bayesian Networks as a Framework for Efficient Bayesian Modeling and Inference, IEEE Transactions on Medical Imaging, vol.23, issue.8, pp.959-967, 2004. ,
DOI : 10.1109/TMI.2004.831221
URL : https://hal.archives-ouvertes.fr/cea-00333687
Dynamics of blood flow and oxygenation changes during brain activation: The balloon model, Magnetic Resonance in Medicine, vol.77, issue.6, pp.855-864, 1998. ,
DOI : 10.1002/mrm.1910390602
Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics, NeuroImage, vol.12, issue.4, pp.466-477, 2000. ,
DOI : 10.1006/nimg.2000.0630
Modeling the hemodynamic response to brain activation, NeuroImage, vol.23, pp.220-233, 2004. ,
DOI : 10.1016/j.neuroimage.2004.07.013
A state-space model of the hemodynamic approach: nonlinear filtering of BOLD signals, NeuroImage, vol.21, issue.2, pp.547-567, 2004. ,
DOI : 10.1016/j.neuroimage.2003.09.052
EEG-fMRI Fusion of Non-Triggered Data Using Kalman Filtering, 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006., pp.6-9, 2006. ,
DOI : 10.1109/ISBI.2006.1625106
URL : https://hal.archives-ouvertes.fr/inria-00070260
Comparing hemodynamic models with DCM, NeuroImage, vol.38, issue.3, pp.387-401, 2007. ,
DOI : 10.1016/j.neuroimage.2007.07.040
URL : http://doi.org/10.1016/j.neuroimage.2007.07.040
fMRI activation maps based on the NN-ARx model, NeuroImage, vol.23, issue.2, pp.680-697, 2004. ,
DOI : 10.1016/j.neuroimage.2004.06.039
An ARX model-based approach to trial by trial identification of fMRI-BOLD responses, NeuroImage, vol.37, issue.1, pp.189-201, 2007. ,
DOI : 10.1016/j.neuroimage.2007.02.045
Nonlinear estimation of the BOLD signal, NeuroImage, vol.40, issue.2, pp.504-514, 2008. ,
DOI : 10.1016/j.neuroimage.2007.11.024
Dealing with the shortcomings of spatial normalization: Multi-subject parcellation of fMRI datasets, Human Brain Mapping, vol.22, issue.8, pp.678-693, 2006. ,
DOI : 10.1002/hbm.20210
A new representation of fMRI data using anatomo-functional constraints, Proc. 8th HBM, 2002. ,
URL : https://hal.archives-ouvertes.fr/inria-00615928
Exploratory fMRI Analysis without Spatial Normalization, 21st Proceedings of IPMI, 2009. ,
DOI : 10.1023/A:1007665907178
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2836541/pdf
Bilinear dynamical systems, Philosophical Transactions of the Royal Society B: Biological Sciences, vol.21, issue.4, pp.983-993, 2005. ,
DOI : 10.1002/hbm.20000
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1854926
Bayesian deconvolution fMRI data using bilinear dynamical systems, NeuroImage, vol.42, issue.4, pp.1381-1396, 2008. ,
DOI : 10.1016/j.neuroimage.2008.05.052
Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging, IEEE Transactions on Medical Imaging, vol.23, issue.2, pp.137-152, 2004. ,
DOI : 10.1109/TMI.2003.822821
Bayesian fMRI time series analysis with spatial priors, NeuroImage, vol.24, issue.2, pp.350-362, 2005. ,
DOI : 10.1016/j.neuroimage.2004.08.034
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.110.6316
Bayesian fMRI data analysis with sparse spatial basis function priors, NeuroImage, vol.34, issue.3, pp.1108-1125, 2007. ,
DOI : 10.1016/j.neuroimage.2006.10.005
Diffusion-based spatial priors for functional magnetic resonance images, NeuroImage, vol.41, issue.2, pp.408-423, 2008. ,
DOI : 10.1016/j.neuroimage.2008.02.005
Constrained restoration and the recovery of discontinuities, IEEE Trans. Pattern Anal. Mach. Intell, vol.14, issue.3, pp.367-383, 1992. ,
Deterministic edge-preserving regularization in computed imaging, IEEE Transactions on Image Processing, vol.6, issue.2, pp.298-311, 1997. ,
DOI : 10.1109/83.551699
Hidden markov random field model selection criteria based on mean field-like approximations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.9, pp.1089-1101, 2003. ,
DOI : 10.1109/TPAMI.2003.1227985
Variational algorithms for approximate Bayesian inference, 2003. ,
Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2001. ,
DOI : 10.1109/34.969114
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.6806
An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.9, pp.1124-1137, 2004. ,
DOI : 10.1109/TPAMI.2004.60
Compound Gauss-Markov random fields for image estimation, IEEE Transactions on Signal Processing, vol.39, issue.3, pp.683-697, 1991. ,
DOI : 10.1109/78.80887
Auxiliary Variable Methods for Markov Chain Monte Carlo with Applications, Journal of the American Statistical Association, vol.21, issue.442, pp.585-595, 1998. ,
DOI : 10.1080/01621459.1985.10477119
Hidden Markov models and desease mapping, J. Amer. Statist. Assoc, vol.97, issue.460, pp.1-16, 2002. ,
Assessing brain activity through spatial bayesian variable selection, NeuroImage, vol.20, issue.2, pp.802-815, 2003. ,
DOI : 10.1016/S1053-8119(03)00360-4
URL : https://epub.ub.uni-muenchen.de/1697/1/paper_316.pdf
Modelling spatially correlated data via mixtures: a Bayesian approach, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.92, issue.4, pp.805-826, 2002. ,
DOI : 10.1111/1467-9868.00288
Mixture models with adaptive spatial regularization for segmentation with an application to FMRI data, IEEE Transactions on Medical Imaging, vol.24, issue.1, pp.1-11, 2005. ,
DOI : 10.1109/TMI.2004.836545
Generalizing Swendsen-Wang to sampling arbitrary posterior probabilities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.8, pp.1239-1253, 2005. ,
DOI : 10.1109/TPAMI.2005.161
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.454.965
Variational bayes inference of spatial mixture models for segmentation, IEEE Transactions on Medical Imaging, vol.25, issue.10, pp.1380-1391, 2006. ,
DOI : 10.1109/TMI.2006.880682
Probabilistic modeling of single-trial fMRI data, IEEE Transactions on Medical Imaging, vol.19, issue.1, pp.19-35, 2000. ,
DOI : 10.1109/42.832957
From Spatial Regularization to Anatomical Priors in fMRI Analysis, IPMI, Glenwood Springs, 2005. ,
DOI : 10.1007/11505730_8
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Transaction on Pattern Analysis and Machine Intelligence, issue.6, pp.721-741, 1984. ,
Nonlinear image recovery with half-quadratic regularization, IEEE Transactions on Image Processing, vol.4, issue.7, pp.932-946, 1995. ,
DOI : 10.1109/83.392335
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.7349
Spatial Mixture Modelling for the Joint Detection-Estimation of Brain Activity in fMRI, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, pp.325-328, 2007. ,
DOI : 10.1109/ICASSP.2007.366682
URL : https://hal.archives-ouvertes.fr/hal-00408628
Spatial mixture modeling of fMRI data, Human Brain Mapping, vol.4, issue.4, pp.233-248, 2000. ,
DOI : 10.1002/1097-0193(200012)11:4<233::AID-HBM10>3.0.CO;2-F
Estimation of Binary Markov Random Fields Using Markov chain Monte Carlo, Journal of Computational and Graphical Statistics, vol.15, issue.1, pp.207-227, 2006. ,
DOI : 10.1198/106186006X97817
Cerebral mechanisms of word masking and unconscious repetition priming, Nat. Neurosci, vol.4, issue.7, pp.752-758, 2001. ,
URL : https://hal.archives-ouvertes.fr/hal-00349842
Modelling the neurovascular habituation effect on fMRI time series, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.433-436, 2009. ,
DOI : 10.1109/ICASSP.2009.4959613
Simulating ratios of normalizing constants via a simple identity: a theoretical exploration, Statistica Sinica, vol.6, pp.831-860, 1996. ,
Fully Bayesian estimation of Gibbs hyperparameters for emission computed tomography data, IEEE Transactions on Medical Imaging, vol.16, issue.5 ,
DOI : 10.1109/42.640741
Simulating normalizing constants: from importance sampling to bridge sampling to path sampling, Statistical Science, vol.13, issue.2, pp.163-185, 1998. ,
DOI : 10.1214/ss/1028905934
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.44.183
Bilinear extrapolation scheme for fast estimation of 3D ising field partition function. Application to fMRI time course analysis, 16th Proc. IEEE ICIP, 2009. ,
Robust Extrapolation Scheme for Fast Estimation of 3D Ising Field Partition Functions: Application to Within-Subject fMRI Data Analysis, 12thProc. MICCAI'09, ser, pp.975-983, 2009. ,
DOI : 10.1007/978-3-642-04268-3_120
URL : https://hal.archives-ouvertes.fr/cea-00470658
Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1, Nature Neuroscience, vol.33, issue.4, pp.569-577, 2006. ,
DOI : 10.1038/nn1675
Schéma d'extrapolation de fonctions de partition de champs de potts. application à l'analyse d'images en IRMf, Actes du 22 e colloque GRETSI, 2009. ,
Monte Carlo strategies in scientific computing, ser. Springer series in Statistics, 2001. ,
Anatomofunctional description of the brain: a probabilistic approach, Proc. 31th Proc. IEEE ICASSP, pp.1109-1112, 2006. ,
Probabilistic anatomo-functional parcellation of the cortex: how many regions, 11thProc. MICCAI, 2008. ,
URL : https://hal.archives-ouvertes.fr/inria-00502805
A General Statistical Analysis for fMRI Data, NeuroImage, vol.15, issue.1, pp.1-15, 2002. ,
DOI : 10.1006/nimg.2001.0933
Constrained linear basis sets for HRF modelling using Variational Bayes, NeuroImage, vol.21, issue.4, pp.1748-1761, 2004. ,
DOI : 10.1016/j.neuroimage.2003.12.024
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.3397
Modern Spectral Estimation, 1988. ,
Unsupervised Bayesian 3D reconstruction for non-destructive evaluation using gammagraphy, EUSIPCO, 2008. ,
Constrained monte carlo maximum likelihood for dependent data, J. Roy. Statist. Soc, vol.54, pp.657-699, 1992. ,
Nonuniversal critical dynamics in Monte Carlo simulations, Physical Review Letters, vol.58, issue.2, pp.86-88, 1987. ,
DOI : 10.1103/PhysRevLett.58.86
Spatial Bayesian Variable Selection With Application to Functional Magnetic Resonance Imaging, Journal of the American Statistical Association, vol.102, issue.478, pp.417-431, 2007. ,
DOI : 10.1198/016214506000001031
Generalization of the Fortuin-Kasteleyn-Swendsen-Wang representation and Monte Carlo algorithm, Physical Review D, vol.38, issue.6, pp.2009-2012, 1988. ,
DOI : 10.1103/PhysRevD.38.2009
Generalizing Swendsen???Wang for Image Analysis, Journal of Computational and Graphical Statistics, vol.16, issue.4, pp.877-900, 2007. ,
DOI : 10.1198/106186007X255144
Multivariate Spatial Gaussian Mixture Modeling for statistical clustering of hemodynamic parameters in functional MRI, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.445-448, 2009. ,
DOI : 10.1109/ICASSP.2009.4959616
Polynomial-Time Approximation Algorithms for the Ising Model, SIAM Journal on Computing, vol.22, issue.5, pp.1087-1116, 1993. ,
DOI : 10.1137/0222066
Dissociating Neural Correlates of Cognitive Components in Mental Calculation, Cerebral Cortex, vol.11, issue.4, pp.350-359350, 2001. ,
DOI : 10.1093/cercor/11.4.350
Sensitivity analysis of parcellation in the joint detection-estimation of brain activity in fMRI, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.568-571, 2008. ,
DOI : 10.1109/ISBI.2008.4541059
Improved fMRI group studies based on spatially varying non-parametric BOLD signal modeling, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1263-1266, 2008. ,
DOI : 10.1109/ISBI.2008.4541233
Bayesian blind separation of generalized hyperbolic processes in noisy and underdeterminate mixtures, IEEE Transactions on Signal Processing, vol.54, issue.9, pp.3257-3269, 2006. ,
DOI : 10.1109/TSP.2006.877660
URL : https://hal.archives-ouvertes.fr/hal-00400662